Gramian Consulting

Business Analyst

• Perform side-by-side (SxS) evaluations on GHD, comparing outputs and assessing quality, accuracy, and relevance.
• Conduct fact-checking to validate information and identify inconsistencies or inaccuracies.
• Provide detailed, well-structured justifications to support evaluation decisions.
• Follow established evaluation guidelines and quality standards consistently.
• Use browser-based tools and extensions to support analysis and review tasks.
• Execute simple command-line instructions when required to support evaluation workflows.
• Document findings clearly and communicate insights to stakeholders when needed.

Business Analyst, AI Evaluation Skills

Field Engineer

• Hardware & Software Field Testing
• Stress Testing: Put multiple wearable devices through their paces in different conditions (speed, temperature, humidity, dust, lighting etc).
• On-site Debugging: Troubleshoot data capture, connectivity, ergonomics, battery life, and software crashes in real-time to minimize downtime.
• Feedback & Product Iteration
• UX/Ergonomics Feedback: Collect detailed feedback from human demonstrators regarding wearable weight, comfort, interference, and heat dissipation during long shifts.
• Technical Reporting: Create structured testing reports to help teams prioritize key fixes and feature requests.
• Feature Validation: Act as the first user for new software features or hardware mods before they are rolled out to the broader operator fleet.
• SOP Design & Optimization
• Process Engineering: Work with the operational team to design the most efficient way to charge, sync, and deploy multiple wearables simultaneously.
• Data Quality Control: Monitor & analyse incoming data streams for quality issues and share feedback & insights with the technical team to help resolve these.
• Training: Build technical training manuals and train non-technical operators on how to handle and maintain the hardware.

AI Engineer

• Design and implement end-to-end data pipeline architecture spanning edge devices, ingestion, processing, storage, and delivery into analytics/AI workloads
• Build scalable ETL and data processing frameworks with orchestration, schema management, versioning, and automated data quality controls
• Develop real-time and streaming infrastructure supporting event-driven systems, edge-to-cloud synchronization, buffering strategies, and strict latency requirements
• Own DevOps and infrastructure engineering, including CI/CD pipelines, infrastructure-as-code, container orchestration, and production deployment workflows
• Implement and maintain security architecture across the stack, including access controls, secrets management, network segmentation, vulnerability scanning, and compliance practices
• Establish strong observability, monitoring, and operational tooling for distributed systems running across cloud, edge, and enterprise integrations
• Support onboarding of complex multimodal data sources including telemetry, time-series, video, audio, LiDAR, and geospatial datasets

Founding Engineer – Industrial AI Platform, Data Infrastructure

QA Engineer

• Review requirements, specifications, and design documents — provide timely feedback on testability and quality concerns.
• Design, document, and execute comprehensive **test plans, test cases, and test suites** (functional, integration, regression, API, UI, usability, etc.).
• Perform manual testing for web and mobile applications — including cross‑browser, cross‑device, and edge‑case testing.
• Validate that features meet business requirements and acceptance criteria before release.
• Identify, document, track, and follow-up on defects — from detection to resolution, ensuring clear reproduction steps and impact assessment.
• Perform regression testing after fixes or new releases to prevent introduced defects.
• Collaborate closely with Developers, Product Managers, and other stakeholders in Agile/Scrum development cycles to ensure QA integration and shared understanding of quality standards.
• Maintain test documentation, defect logs, and QA reports; track QA metrics (e.g. defect density, open defect count, pass/fail rate) to measure product quality and help continuous improvement.
• Participate in performance, load or stress testing and data‑integrity testing when required.
• Mentor or guide junior QA or testing staff — share best practices in test design, documentation, and QA process.

Senior QA / Testing Engineer

Backend Engineer

• Write unit tests for new features developed by other engineers
• Maintain the databases and services that power the backend of our product
• Coordinate with other teams to ensure that there are no conflicts between backend systems and third party applications.
• Maintain a high level of service by identifying potential performance bottlenecks before they happen.
• Work closely with our product managers to determine what data is needed to build features or provide analytics on our users.
• Assist with any tasks related to ensuring the integrity of our user data.

Senior Backend Engineer, Python, Docker, Kubernetes

DevOps Engineer

• Provide Level 2+ technical support across **multi-cloud public environments** (AWS, GCP, OCI, OVH, and occasionally Azure)
• Manage incidents and service requests through ITSM tools in compliance with ITIL processes
• Operate and maintain Linux-based cloud infrastructures
• Perform daily operational activities (monitoring, backups, patching, health checks)
• Diagnose and resolve IaaS / PaaS infrastructure incidents
• Update and enhance technical documentation and knowledge bases
• Apply and promote cloud security and operational best practices
• Participate in technical committees and client steering meetings
• Collaborate with project teams during deployment and evolution phases
• Contribute to cloud advisory and expertise missions
• Stay up to date with emerging cloud technologies and share knowledge internally

Cloud Operations Engineer, Multi-Cloud Environments

Operations

• Lead and manage daily operations of the Service Desk team
• Act as technical escalation point and subject-matter reference
• Coordinate communication between clients and internal technical teams
• Ensure SLA adherence, incident resolution, and service quality standards
• Support team development through coaching, feedback, and performance management
• Contribute to process improvement and operational efficiency initiatives
• Participate in reporting (weekly/monthly/quarterly as required)
• Support transition activities and evolving team responsibilities